NeTS: Small: Collaborative Research: Distributed Robust Spectrum Sensing and Sharing in Cognitive Radio Networks

NetS：小型：协作研究：认知无线电网络中的分布式鲁棒频谱感知和共享

• 批准号: 1464092
• 负责人: Jie Yang
• 金额: $ 13.47万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464092&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; Distributed

The future Cognitive Radio Networks (CRNs) will consist of heterogeneous devices such as smartphones, tablets and laptops moving dynamically. Accurate and robust spectrum sensing and identification of unauthorized spectrum usage are essential components of spectral efficiency in future radio systems. This project aims to utilize consensus-based cooperation featuring self-organizable and scalable network structure to capture the swarming behaviors of spectrum users and providing cooperative spectrum sensing in a fully distributed manner. By using a combination of control theory and machine learning techniques, the project designs secure weighted average consensus for cooperative spectrum sensing that can not only capture the swarming behaviors in CRNs with heterogeneous devices, but also is robust to practical channel conditions. Robust localization approaches are developed grounded on dynamic signal strength mapping, which have the capability to localize multiple malicious users. Additionally, the new techniques are validated using an actual testbed with on-campus deployment and system demonstration to industrial collaborators. The integration of control theory with dynamic spectrum access will enable a new revolution in the way for enhancing spectrum efficiency in CRNs. The project serves as a pioneer in exploiting multi-disciplinary knowledge (e.g., control systems and machine learning techniques) to achieve a more efficient spectrum usage in future radio systems, aiming to alleviate the increasing crowdness of the spectrum occupancy and support the co-existence of heterogeneous devices. This project also carries out a broad range of education and outreach activities to encourage students to pursue careers in the fields of science and engineering. Research results will be disseminated to academia and industry through presentations and publications in meetings, conferences and journals.

未来的认知无线电网络（CRN）将由异质设备（例如智能手机，平板电脑和笔记本电脑动态移动）组成。准确，稳健的光谱传感和未经授权光谱使用情况的识别是未来无线电系统中光谱效率的重要组成部分。该项目旨在利用基于共识的合作，以可自组织和可扩展的网络结构为特色，以捕获频谱用户的蜂群行为，并以完全分布的方式提供合作频谱感知。通过使用控制理论和机器学习技术的结合，该项目设计了合作频谱传感的安全加权平均共识，这些共识不仅可以捕获具有异构设备的CRN中的蜂群行为，而且对实际的渠道条件也很强。强大的本地化方法是建立在动态信号强度映射的基础上的，该方法具有定位多个恶意用户的能力。此外，使用校园内部部署和系统演示的实际测试台对新技术进行验证。控制理论与动态频谱访问的整合将在提高CRN的频谱效率方面进行新的革命。该项目是利用多学科知识（例如控制系统和机器学习技术）的开拓者，以实现未来无线电系统中更有效的光谱使用情况，旨在减轻频谱占用的人群的增加并支持异类式载体的共存。该项目还开展了广泛的教育和外展活动，以鼓励学生从事科学和工程领域的职业。研究结果将通过会议，会议和期刊的演讲和出版物传播到学术界和行业。